The subject matter disclosed herein relates to condition monitoring systems and, more particularly, to embodiments of a condition monitoring system and method that arrange data on an interface based on fault condition.
Although preventive maintenance can reduce the occurrence of machine breakdown, it also has some problems. First, the appropriate period between maintenance procedures is very difficult to determine because machines and their components do not necessarily fail at regular intervals. Second, production time is lost because it is prudent to examine as many components as possible during the maintenance period. Third, parts in reasonable condition are often replaced unnecessarily.
Machine monitoring and diagnostics can be seen as a decision-support tool which is capable of identifying the cause of failure in a machine component or system, as well as predicting its occurrence from a symptom. Without accurate direction and identification of the machine fault, maintenance and production scheduling cannot be effectively planned and the necessary repair task cannot be carried out in time. Therefore, machine monitoring and diagnostics is essential for an effective predictive maintenance program.
The ultimate goal of using machine monitoring and diagnostics is to increase equipment availability, and in addition, reduce maintenance and unexpected machine breakdown costs. In order to maximize availability, one has to increase reliability by maximizing the machine uptime and, at the same time, increase maintainability by minimizing the mean time to repair. As a result of constant monitoring and diagnostics, the frequency of unexpected machine breakdown is significantly reduced, and machine problems can be pinpointed immediately.
Machine monitoring and diagnostics can be done by simply listening to the sound generated during machine operation or visually examining the quality of machined parts to determine machine condition. In such a situation, however, the identification of a machine fault is totally dependent on the experience of the operator or engineer. Besides, many machine faults are not accurately assessed by relying only on visual or aural observations, especially during operation (e.g., wear and crack in bearings and gearboxes). Therefore, more sophisticated signal processing techniques, such as vibration analysis, oil analysis, acoustic emission, infrared, and ultrasound, have been developed to help the maintenance technician and engineer detect and diagnose machine failures.
The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.